Hello,
I'm working on a transect SECR and have run into some issues with fitting the model. I'm not using any covariates at the moment, just trying to get a general idea. We have 18 transects/detectors, 37 unique individuals, 3 occasions, and 135 detections. When I run the model using method='Nelder-Mead' I get a density estimate of 1.7e-21 and a lambda0 of 1.48e+40. I tried with the default model and received a much more realistic density estimate (~0.02) but lambda is still huge and the variances fail to compute for both lambda and sigma. Any suggestions?
Here is the code I'm using:
layer <- readOGR('OG_Transects.shp')
transects <- read.traps("OG_Detections_Scat.txt",detector='transect')
detections <- read.table("OG_Events_Scat.txt")
detections <- detections[,c(1:5)]
CH <- make.capthist(detections,transects, fmt="XY",tol=50,snapXY=T,noccasions=3)
transectmask <- make.mask(transects, type='trapbuffer',buffer=740, spacing=185)
results <- secr.fit(CH,mask=transectmask,binomN=0,method='Nelder-Mead',trace=FALSE,verify=F, start=list(D=0.001, g0=0.1, sigma=200))
Thank you!